Manager, Market Access Data & Delivery Lead

India

Actively hiring, first seen by us today

Pay: Pay not listed
Work setting: Not stated
Employment: Not stated

What you’ll work on

Full posting

This role is the technical and delivery counterpart to the US AI project lead.

Data products and data foundation- Build data products for Market Access, moving data from CSCAN into Databricks.

Build Market Access data products, moving data from CSCAN into Databricks
Transition the current BoW into the gold layer in Databricks
Build the semantic and context layer with CBIT and keep data definitions consistent
Run evaluation, data quality checks and monitoring for data products and AI outputs
Act as single point of contact in Hyderabad across AI initiatives and vendors

From the employer’s posting

This role is the technical and delivery counterpart to the US AI project lead. You are the Hyderabad lead for the team's AI work: building the data products that the AI capability runs on, shaping the semantic and context layer with CBIT, and keeping data quality and evaluation under control. You are also the Hyderabad point of contact across the AI initiatives, working with Data Strategy, CBIT and vendors. The role needs hybrid depth: strong data and AI skills, plus enough market access knowledge to build the right context.Responsibilities

Data products and data foundation- Build data products for Market Access, moving data from CSCAN into Databricks.

Build data products for Market Access, moving data from CSCAN into Databricks.

Transition the current BoW into the gold layer in Databricks.

Build the semantic and context layer with CBIT, using the market access context and metric definitions gathered by the US lead and the brand-focused team members.

Run evaluation, data quality checks and monitoring for the data products and the AI outputs built on them.

Act as the single point of contact in Hyderabad across the AI initiatives, aligning timelines and data products.

What you’ll bring

All qualifications

Core experience

Experience with syndicated and gross-to-net data.
Familiarity with enterprise AI assistants such as Claude.
Experience working with onshore teams across US and India time zones.

Qualification wording

Experience with syndicated and gross-to-net data.

Familiarity with enterprise AI assistants such as Claude.

Experience working with onshore teams across US and India time zones.

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Posting record

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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Nov 3, 2026today
Recorded sightings: 2
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 0

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From 7,797 similar postings that came down. Coming down is not always a hire.

KMK Consulting is hiring

12 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Data Leadership hiring is picking up
Its jobs tend to stay up a long time

Hiring record

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Where the posting names them

This role is the technical and delivery counterpart to the US AI project lead. You are the Hyderabad lead for the team's AI work: building the data products that the AI capability runs on, shaping the semantic and context layer with CBIT, and keeping data quality and evaluation under control. You are also the Hyderabad point of contact across the AI initiatives, working with Data Strategy, CBIT and vendors. The role needs hybrid depth: strong data and AI skills, plus enough market access knowledge to build the right context.Responsibilities Data products and data foundation- Build data products for Market Access, moving data from CSCAN into Databricks. - Transition the current BoW into the gold layer in Databricks.

Data products and data foundation- Build data products for Market Access, moving data from CSCAN into Databricks. - Transition the current BoW into the gold layer in Databricks. - Handle ingestion into the database and create the data models the AI capability depends on, working to the data design the team provides.

Requirements - Data and product development: experience building data products on Databricks, including curated (gold) layers, and taking them from concept through release and scale. [Years of experience to be confirmed] - AI and agentic architecture: working knowledge of agent frameworks, semantic layers, guardrails and evaluation.

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About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025: $175,140
Expected change, 2025 to 2035: 15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

Role summary

This role is the technical and delivery counterpart to the US AI project lead. You are the Hyderabad lead for the team's AI work: building the data products that the AI capability runs on, shaping the semantic and context layer with CBIT, and keeping data quality and evaluation under control. You are also the Hyderabad point of contact across the AI initiatives, working with Data Strategy, CBIT and vendors. The role needs hybrid depth: strong data and AI skills, plus enough market access knowledge to build the right context.

Responsibilities

Data products and data foundation

Build data products for Market Access, moving data from CSCAN into Databricks.
Transition the current BoW into the gold layer in Databricks.
Handle ingestion into the database and create the data models the AI capability depends on, working to the data design the team provides.

Semantic and context layer

Build the semantic and context layer with CBIT, using the market access context and metric definitions gathered by the US lead and the brand-focused team members.
Keep data definitions consistent across brands, personas and AI initiatives.

Quality, evaluation and support

Run evaluation, data quality checks and monitoring for the data products and the AI outputs built on them.
Provide documentation and ongoing support for the data products.

Coordination

Act as the single point of contact in Hyderabad across the AI initiatives, aligning timelines and data products.
Lead from Hyderabad for Data Strategy, CBIT and vendors.
Work closely with the Market Access Analytics lead and the India team lead, and with the US AI project lead on priorities and releases.

Requirements

Data and product development: experience building data products on Databricks, including curated (gold) layers, and taking them from concept through release and scale. [Years of experience to be confirmed]
AI and agentic architecture: working knowledge of agent frameworks, semantic layers, guardrails and evaluation.
Pharma data sets: understanding of pharmacy and medical benefits data and their limits.
Market access knowledge: enough payer, access and coverage context to build and check the semantic layer; deeper knowledge is a strong plus.
Data quality and monitoring: experience setting up evaluation, quality checks and monitoring.
Project management: coordinating timelines and dependencies across teams and vendors.
Documentation and communication: clear written documentation, and comfort working with business, IT and vendor teams.

Preferred

Experience with syndicated and gross-to-net data.
Exposure to contracting and 340B analytics, which are expected to become workstreams next year.
Familiarity with enterprise AI assistants such as Claude.
Experience working with onshore teams across US and India time zones.

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